Specialist Data Hub

About the Role

The Data Engineer Specialist is a key contributor to DKSHs global data capability responsible for building and sustaining the cloud data platforms that enable data-driven decisions across this role you will shape the integrity and scalability of DKSHs data infrastructure directly supporting business performance and operational excellence on a global scale.

What You Will Deliver

• Design develop and implement end-to-end data pipelines and data integration processes both batch and real-time covering data analysis profiling cleansing lineage mapping transformation and the full deployment of Extract Transform Load / Extract Load Transform (ETL/ELT) solutions.
• Drive continuous improvements in data quality reliability and efficiency by monitoring pipeline performance and optimizing ETL/ELT processes to meet evolving business demands.
• Establish and deliver best practices across the data management lifecycle including modular ETL/ELT development coding and configuration standards error handling auditing and data archival.
• Identify and implement Artificial Intelligence (AI) automation and data-driven innovations that streamline operations reduce manual effort and measurably improve productivity.
• Ensure all development aligns with data governance policies and Business Intelligence (BI) platform guidelines maintaining compliance and consistency across environments.
• Partner with Information Technology (IT) team members Subject Matter Experts (SMEs) vendors and business stakeholders to translate data needs into effective goal-aligned solutions.
• Resolve Business-As-Usual (BAU) data issues and change requests efficiently maintaining thorough documentation of investigations findings recommendations and resolutions.
• Support production monitoring operational incidents and service requests including standby support as required.

What You Bring

• Bachelors degree in Computing Information Technology or equivalent.
• Fresh graduate or up to 1 year of relevant working experience.
• Hands-on experience with Microsoft Fabric including Lakehouse Warehouse Data Pipeline OneLake Notebook and deployment pipelines.
• Practical experience with Azure Data Solutions including Azure Synapse Spark Synapse Database Azure Data Factory Databricks and Azure Data Lake Storage.
• Solid grounding in ETL/ELT frameworks data warehousing concepts data management frameworks and data lifecycle processes.
• Proven ability to handle and process structured semi-structured and unstructured data effectively.
• Proficiency in Python PySpark and Structured Query Language (SQL) for data engineering development.
• Experience using Azure DevOps to implement Continuous Integration and Continuous Deployment (CI/CD) workflows and manage ETL job deployments across multiple environments.
• Strong knowledge of database technologies including Relational Database Management Systems (RDBMS) NoSQL and columnar databases.
• Strong awareness of AI technologies with the ability to apply AI solutions automation and analytics to simplify processes and drive operational efficiency.
• Clear and effective communicator able to present technical concepts to both technical and non-technical audiences.
• Self-driven and collaborative with the ability to work independently and contribute effectively within diverse multi-stakeholder teams.
• High sense of ownership strong affinity for data and a continuous improvement mindset.
• Knowledge of SAP is an added advantage.